• Title/Summary/Keyword: Loudness Metering Algorithm

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A Study on Real-Time Loudness Metering Algorithm for Digital Broadcasting (디지털 방송용 오디오 레벨 계측 알고리즘의 실시간화 연구)

  • Park Seong-Gyoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.16 no.4 s.95
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    • pp.427-437
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    • 2005
  • In this paper, the perceived audio level metering algorithm of digital audio sound to be able to operate in real-time is proposed. Through analyzing a conventional recommendation ITU-RBS1387-I for objective audio quality analysis, FFT-based loudness metering algorithm is implemented and the real-time method of that algorithm was advised and proved. The proposed method is based on look-up table. In order to prove the proved method, using 23 pure tones and 30 preselected digital audio samples, its performance and operation time is evaluated. Its performance, compared with an original algorithm's, have a good figure of less than $2\;\%$ error even if look-up table related with spectral spreading have large level resolution of $10\;\cal{dB}$. The proposed algorithm take only 1/21 of original algorithm's measuring time. Also, in the proposed algorithm auditory pitch group energy calculation take 1/450 of original algorithm's and excitation calculation take 1/3.57. In conclusion, the proposed algorithm is expected to be implemented into DSP-based real-time loudness meter.

Performance analysis of subjective Loudness meter with ITU-R BS. 1387-1 algorithm for digital audio (디지털 오디오 주관적 음향레벨 계측기 구현을 위한 ITU-R BS. 1387-1의 알고리즘 특성 분석)

  • Ngan, Nguyen Vo Bao;Park, Seonggyoon;Ro, Soonghwan;Han, Chankyu
    • Journal of IKEEE
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    • v.16 no.4
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    • pp.395-404
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    • 2012
  • In this paper, the perceived loudness metering algorithm based on ITU-R BS.1387-1 was investigated and implemented, and its performance was evaluated by applying to 23 pure tones and 9 digital audio samples. Error of the tone test results compared with ISO226:2003 was below 5%, and sample test results, in comparison with Moore's algorithm, showed deviation of less than 4.7% and correlation of 0.96. On the other hand, it was investigated how the implemented algorithm's performance was subject to auditory pitch scale. Its result showed that the algorithm with 37 auditory filters, through correcting a bias effect, has a good performance of less than 2% in comparison with the one with 109 auditory filters.